Open AccessResponse Surface Design for Removal of Lead by Different Lactic Acid Bacteria
Author(s) -
Leila Goudarzi,
R Kasra Kermanshahi,
Gholamreza Jahed Khaniki
Publication year - 2020
Publication title -
health scope
Language(s) - English
Resource type - Journals
eISSN - 2251-9513
pISSN - 2251-8959
DOI - 10.5812/jhealthscope.101049
Subject(s) - response surface methodology , central composite design , lead (geology) , lactobacillus acidophilus , plackett–burman design , heavy metals , pulp and paper industry , bacteria , chemistry , environmental science , food science , environmental chemistry , biology , chromatography , probiotic , paleontology , genetics , engineering
Background: Toxic heavy metals, such as lead, are widely used in industry and may cause serious health problems and ecological hazards for living organisms. Objectives: The current study aimed to investigate the removal efficiency of lead by Lactobacillus strains using a methodological approach. Methods: After selecting the bacteria with the maximum metals removal ability, experiments were conducted according to (i) the Plackett-Burman design (Minitab18 program) to screen several significant process factors and (ii) Central Composite Design (Design-Expert 11.1.2.0 program) to find out the optimum process conditions for the maximum capacity of metal removal efficiency. Results: The optimum pH, metal, and bacterial concentration were 6.76, 391 mg.L-1, and 4.60 g.L-1 for lead removal ability of L. acidophilus ATCC4356. A quadratic model was developed to correlate the variables with removal efficiency. According to the results, this model was not statistically significant (P > 0.05). Conclusions: The experimental removal efficiencies at the optimum condition for lead by L. acidophilus ATCC4356 (73.9%) were consistent with the predicted values. Consequently, due to their appreciate efficiency and the lower cost of the lead removal ability, these two bacteria may be a candidate as good biosorbents. The results also confirmed that the Response Surface Methodology is an appropriate methodology for modeling of removal efficiency.